Market hype and growing interest in artificial intelligence (AI) are pushing established software vendors to introduce AI into their product strategy, creating considerable confusion in the process.
Analysts predict that by 2020, AI technologies will be virtually pervasive in almost every new software product and service.
Similar to greenwashing, in which companies exaggerate the environmental-friendliness of their products or practices for business benefit, many technology vendors are now “AI washing” by applying the AI label a little too indiscriminately, according to Gartner. This widespread use of “AI washing” is already having real consequences for investment in the technology.
Analysts predict that by 2020, AI will be a top five investment priority for more than 30 percent of CIOs. In January 2016, the term “artificial intelligence” was not in the top 100 search terms on gartner.com. By May 2017, the term ranked at No. 7, indicating the popularity of the topic and interest from the clients in understanding how AI can and should be used as part of their digital business strategy.
“As AI accelerates up the Hype Cycle, many software providers are looking to stake their claim in the biggest gold rush in recent years,” said Jim Hare, research vice president at Gartner. “AI offers exciting possibilities, but unfortunately, most vendors are focused on the goal of simply building and marketing an AI-based product rather than first identifying needs, potential uses and the business value to customers.”
But, to successfully exploit the AI opportunity, technology providers need to understand how to respond to three key issues:
Lack of differentiation is creating confusion and delaying purchase decisions
The huge increase in startups and established vendors all claiming to offer AI products without any real differentiation is confusing buyers. More than 1,000 vendors with applications and platforms describe themselves as AI vendors, or say they employ AI in their products.
To build trust with end-user organizations vendors should focus on building a collection of case studies with quantifiable results achieved using AI.
Proven, less complex machine-learning capabilities can address many end-user needs
Advancements in AI, such as deep learning, are getting a lot of buzz but are obfuscating the value of more straightforward, proven approaches. Gartner recommends that vendors use the simplest approach that can do the job over cutting-edge AI techniques.
Organizations lack the skills to evaluate, build and deploy AI solutions
More than half the respondents to Gartner’s 2017 AI development strategies survey indicated that the lack of necessary staff skills was the top challenge to adopting AI in their organization. If they had a choice, most organizations would prefer to buy embedded or packaged AI solutions rather than trying to build a custom solution.
“Software vendors need to focus on offering solutions to business problems rather than just cutting-edge technology,” said Hare. “Highlight how your AI solution helps address the skills shortage and how it can deliver value faster than trying to build a custom AI solution in-house.”